Developments in information technology and its prevalent growth in several areas of business, engineering, medical, and scientific studies are resulting in information as well as data explosion. Knowledge discovery and decision making from such rapidly growing voluminous data are a challenging task in terms of data organization and processing, which is an emerging trend known as big data computing. Big data has gained much attention from the academia and the IT industry. A new paradigm that combines large-scale compute, new data-intensive techniques, and mathematical models to build data analytics. Thus, this chapter discusses the background of big data. It also discusses the various application of big data in detail. The various related work and the future direction would be addressed in this chapter.
Top2. Background
In day-to-day life millions and billions of data are created everyday by people be it on any social networking sites, finance, medicine, sensors, mobile applications and so on. To manage, analyze and process all these data new processing methodologies, techniques and tools must be used. The information's are being flooded and are beyond a range, in which it cannot to measure. A best example is Facebook, where 100 Terabytes of data are uploaded every day. The term “Big data” came into emergence to store and process huge amount of data in a simple way. There are various definitions of big data stated by researches. According to McKinsey, Big data is a huge amount of data in which the size of the data is beyond the size of regular databases. O’Reilly states that big data is nothing but the data that exceeds the limit of normal database where the data or information is large and processed quickly. Hence new approaches have to be followed to process the information. According to Gartner, Enormous data means high volume, rapid speed and variety of data resources which needs new procedures and techniques to handle the data. New approaches and techniques is difficult to apply on traditional databases by using simple software tools used in accessing the relational database. Data can be both structured as well as unstructured data collected from different resources. All the definitions lead to 5 V’s which is Volume, Velocity, Variety, Veracity, Value.
Hence new approaches have to be followed to process the information. According to Gartner, Enormous data means high volume, rapid speed and variety of data resources which needs new procedures and techniques to handle the data. New approaches and techniques is difficult to apply on traditional databases by using simple software tools used in accessing the relational databases database. Data can be both structured as well as unstructured data collected from different resources (Sunny Sharma et al., 2016). All the definitions lead to 5 V’s which is Volume, Velocity, Variety, Veracity, Value.